{"files"=>["https://ndownloader.figshare.com/files/5211727"], "description"=>"<p>A: Neuronal responses are related to the external event (in this example stimulus; S), but are triggered (R) by an internal process, which is not precisely time-locked to the onset of the event. B: A certain amount of noise is recorded together with the relevant neuronal responses. C: During the experiment, the external event occurs multiple times, while the neuronal activity is recorded. D: When neuronal responses are aligned on the response start, the trial average response (F: blue line) is a good approximation of the real neuronal response. However, the response onset is unknown. The trial-averaged response aligned on the event onset triggers (F: red line) does not correctly reproduce the real neuronal response. In addition, the standard deviation across trials calculated using the event onset triggers (F: blue and red shaded tubes) is an incorrect estimate of the variability of neuronal responses. This example was generated using Gaussian white noise with a standard deviation equal to 5% of the maximum response amplitude (SNR = 20). Differences between the response starts and stimulus onsets were modelled using a Gaussian distribution with a standard deviation equal to 1/7 of the response standard deviation (<i>σ</i><sub><i>R</i></sub> = 700ms, <i>σ</i><sub><i>J</i></sub> = 100ms).</p>", "links"=>[], "tags"=>["parameter values", "jittered", "influence", "interpretation", "data", "analysis", "efficacy", "trigger", "Such", "behaviour", "Optimization", "realignment algorithm", "performance", "Variance", "Temporal jitter", "realignment algorithms", "stimulus", "dTAV", "signal", "variance", "estimation", "Parametric Realignment Algorithms Neuronal responses", "stimuli"], "article_id"=>3369265, "categories"=>["Neuroscience", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Tomislav Milekovic", "Carsten Mehring"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0153773.g001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Effect_of_single_trial_jitter_on_the_estimation_of_the_underlying_neuronal_response_/3369265", "title"=>"Effect of single trial jitter on the estimation of the underlying neuronal response.", "pos_in_sequence"=>1, "defined_type"=>1, "published_date"=>"2016-05-09 06:10:22"}

{"files"=>["https://ndownloader.figshare.com/files/5211745"], "description"=>"<p>Data obtained by simulating 2000 100-trial experiments. A: Expectation of <i>dTAV</i> as a function of the reduction of jitter standard deviation. Lines drawn only for values of SNR of 0.2 and higher. For lower SNR, 2000 repetitions were insufficient to provide a reliable estimate of the expected value of <i>dTAV</i> due to the high noise level. For the shown SNR range, the expected value of <i>dTAV</i> is independent of the SNR. B: The standard deviation (std) of <i>dTAV</i> as a function of the amount of jitter reduction for different SNRs. Standard deviations of <i>dTAV</i> for SNR of 0.2 and lower are above 10<sup>−6</sup> and are, therefore, not shown. C: Probability of jitter reduction as a function of <i>ndTAV</i> for different SNRs. Panels A, B and C are shown for integration time <i>T</i><sub><i>I</i></sub> of 300ms. D: Values of jitter reduction and integration times for which the probability of correct <i>dTAV</i> prediction reaches 90%. For jitter reductions and integration times above the line, the probability for correct <i>dTAV</i> prediction, , is above 90%. For SNRs of 0.13 and lower, the probability of correct <i>dTAV</i> prediction never reached 90%.</p>", "links"=>[], "tags"=>["parameter values", "jittered", "influence", "interpretation", "data", "analysis", "efficacy", "trigger", "Such", "behaviour", "Optimization", "realignment algorithm", "performance", "Variance", "Temporal jitter", "realignment algorithms", "stimulus", "dTAV", "signal", "variance", "estimation", "Parametric Realignment Algorithms Neuronal responses", "stimuli"], "article_id"=>3369283, "categories"=>["Neuroscience", "Biological Sciences not elsewhere classified", "Science Policy"], "users"=>["Tomislav Milekovic", "Carsten Mehring"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0153773.g003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Reliability_of_i_dTAV_i_as_a_measure_of_jitter_reduction_for_mono-phasic_neuronal_responses_/3369283", "title"=>"Reliability of <i>dTAV</i> as a measure of jitter reduction for mono-phasic neuronal responses.", "pos_in_sequence"=>3, "defined_type"=>1, "published_date"=>"2016-05-09 06:10:22"}